AI Costs Surpass Human Labor: Insight from Nvidia and MIT
Artificial intelligence (AI) continues to reshape industries and workplaces, but recent insights reveal that, contrary to popular belief, AI is currently more expensive than employing human workers. Bryan Catanzaro, vice president of applied deep learning at Nvidia, stated that for his team, the cost of AI compute significantly exceeds the cost of the employees themselves. This challenges the common narrative that AI’s primary benefit lies in cutting labor expenses.
Catanzaro’s perspective was highlighted in a recent interview with Axios, where he emphasized the substantial financial demands AI infrastructure requires. This includes high-powered computing resources and energy consumption, which contribute heavily to operational costs.
Economic Viability of AI Automation: Findings from MIT
Supporting this viewpoint, a 2024 study conducted by the Massachusetts Institute of Technology (MIT) evaluated the economic feasibility of AI automation across various job categories. Researchers found that AI automation is financially justified in only about 23% of jobs, primarily those involving extensive visual tasks. For the remaining 77%, retaining human labor remains the economically smarter choice.
The study highlights the complexity behind AI adoption: while AI can perform certain tasks efficiently, many roles still demand human flexibility, judgment, and cost-effectiveness. This nuance is critical for businesses considering AI integration and workforce restructuring.
Heavy Investments Amid Uncertain Returns
Despite these cost challenges, major technology companies are aggressively investing in AI. According to Morgan Stanley, the tech sector has committed approximately $740 billion to AI-related expenditures in 2026, marking a 69% increase from the previous year. Additionally, the rising costs of AI software—growing between 20% and 37% as reported by spending management firm Tropic—further underscore the significant financial commitment involved.
These investments extend beyond software to massive infrastructure spending. McKinsey estimates project AI-related expenses could soar to $5.2 trillion by 2033, including $1.6 trillion for data centers and $3.3 trillion for IT hardware. Such scale suggests that companies anticipate long-term benefits despite current economic mismatches.
However, the rapid growth in AI spending has led some companies to re-evaluate their budgets. Uber’s chief technology officer, Praveen Neppalli Naga, recently disclosed that AI-driven coding tools have inflated project costs beyond initial expectations, necessitating budget reconsiderations.
Rising Tech Layoffs Amid AI Expansion
Paradoxically, as AI spending surges, tech layoffs have also increased. Data from Layoffs.fyi indicates that over 92,000 tech workers have been laid off in 2026 across nearly 100 companies, accelerating faster than the approximately 120,000 layoffs recorded throughout 2025. This trend reflects the tension between growing AI investments and workforce reductions.
Keith Lee, an AI and finance professor at the Swiss Institute of Artificial Intelligence’s Gordon School of Business, explains this as a “short-term mismatch” between financial logic and corporate actions. While AI remains more costly than human labor for many functions, companies continue to pour resources into AI development and deployment.
Lee anticipates this dynamic will evolve as AI technology matures, infrastructure improves, and costs decline. True cost-effectiveness, he notes, depends not only on AI becoming cheaper than humans but also on its reliability and predictability at scale.
“It’s not just about AI becoming cheaper than humans,” Lee told Fortune. “It’s about becoming both cheaper and more predictable at scale.”
Key Takeaways
- Nvidia vice president Bryan Catanzaro says that for his team, AI compute now costs more than the employees using it, making AI more expensive than human labor.
- A 2024 MIT study finds AI automation is economically viable in only about 23% of jobs, with humans still cheaper in the remaining 77%.
- Despite unclear productivity gains and high costs, big tech companies have committed around $740 billion to AI-related expenses this year, a 69% jump from 2025.
For a detailed look at the economics of AI adoption and its impact on the workforce, read more here.
